mlx-community/quantized-gemma-2b-it

MacBook Air (Apple M4)

32 GB · macOS 26.3

Tested on March 5, 2026

Top 87% Compare

Global Score

45 /100

Marginal

Hardware Fit

100/100

Quality

21/100

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Hardware

Machine: MacBook Air
CPU: Apple M4
Cores: 10 total (4 perf + 6 eff)
Frequency: 2.4 GHz
RAM: 32 GB LPDDR5
GPU: Apple M4
OS: macOS 26.3
Arch: arm64
Power Mode: balanced

Performance

Tokens/sec Tokens generated per second — higher is better: 44.4
Standard deviation Variation of speed across benchmark runs — lower means more consistent: ±2.5
First chunk latency Delay before the first streamed chunk arrives from runtime: 336 ms
Time to first token How fast the model starts responding — lower is better: 336 ms
Load time Time to load the model into memory before inference: N/A
Memory usage RAM consumed during inference — percentage of total system memory: 0.1 GB (0%)
Total tokens Total number of tokens generated across all benchmark prompts: 1044

Score breakdown

Speed

50/50

Time to first token

20/20

Memory

30/30

Quality

Reasoning

4/20

Coding

1/20

Instruction following

9/20

Structured output

4/15

Math

2/15

Multilingual

1/10

Category levels

Reasoning: Poor Coding: Poor Instruction Following: Weak Structured Output: Weak Math: Poor Multilingual: Poor

Metadata

Spec version: 0.2.1
Runtime: LM Studio 0.4.6+1
Model format: GGUF
Hardware profile: BALANCED
Result hash: a3c0d0647e8cdfeac6d714ca55295f676bb652d3a0cfd2e0c767f6f48e5c922b

Interpretation

Hardware fit: 100/100. Overall suitability: MARGINAL (Global 45/100). Category profile: Reasoning: Poor, Coding: Poor, Instruction Following: Weak, Structured Output: Weak, Math: Poor, Multilingual: Poor.

Bench Environment

Power: AC CPU load: avg 13% (peak 14%)

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